With the advancement of computational power, refinement of learning algorithms and architectures, and availability of big data, artificial intelligence (AI) technology, particularly with machine learning and deep learning, is paving the way for ‘intelligent’ healthcare systems. AI-related research in ophthalmology previously focused on the screening and diagnosis of posterior segment diseases, particularly diabetic retinopathy, age-related macular degeneration and glaucoma. There is now emerging evidence demonstrating the application of AI to the diagnosis and management of a variety of anterior segment conditions. In this review, we provide an overview of AI applications to the anterior segment addressing keratoconus, infectious keratitis, refractive surgery, corneal transplant, adult and paediatric cataracts, angle-closure glaucoma and iris tumour, and highlight important clinical considerations for adoption of AI technologies, potential integration with telemedicine and future directions.

Background/AimsTo compensate the retinal nerve fibre layer (RNFL) thickness assessed by spectral-domain optical coherence tomography (SD-OCT) for anatomical confounders.MethodsThe Singapore Epidemiology of Eye Diseases is a population-based study, where 2698 eyes (1076 Chinese, 704 Malays and 918 Indians) with high-quality SD-OCT images from individuals without eye diseases were identified. Optic disc and macular cube scans were registered to determine the distance between fovea and optic disc centres (fovea distance) and their respective angle (fovea angle). Retinal vessels were segmented in the projection images and used to calculate the circumpapillary retinal vessel density profile. Compensated RNFL thickness was generated based on optic disc (ratio, orientation and area), fovea (distance and angle), retinal vessel density, refractive error and age. Linear regression models were used to investigate the effects of clinical factors on RNFL thickness.ResultsRetinal vessel density reduced significantly with increasing age (1487±214 µm in 40–49, 1458±208 µm in 50–59, 1429±223 µm in 60–69 and 1415±233 µm in ≥70). Compensation reduced the variability of RNFL thickness, where the effect was greatest for Chinese (10.9%; p<0.001), followed by Malays (6.6%; p=0.075) and then Indians (4.3%; p=0.192). Compensation reduced the age-related RNFL decline by 55% in all participants (β=−3.32 µm vs β=−1.50 µm/10 years; p<0.001). Nearly 62% of the individuals who were initially classified as having abnormally thin RNFL (outside the 99% normal limits) were later reclassified as having normal RNFL.ConclusionsRNFL thickness compensated for anatomical parameters reduced the variability of measurements and may improve glaucoma detection, which needs to be confirmed in future studies.

Background and Aims:A decision-to-delivery interval (DDI) of 30 min for category-one caesarean section (CS) deliveries is the standard of practice recommended by clinical guidelines. Our institution established a protocol for category-one (‘crash’) CS to expedite deliveries. The aim of this study is to evaluate DDI, factors that affect DDI and the mode of anaesthesia for category-one CS.Methods:This retrospective cohort study evaluated 390 women who underwent category-one CS in a tertiary obstetric centre. We analysed the factors associated with DDI, mode of anaesthesia and perinatal outcomes. Summary statistics were performed for the outcomes. The association factors were considered significant at P < 0.05.Results:The mean (standard deviation) DDI was 9.4 (3.2) min with all deliveries achieved within 30 min. The longest factor in the DDI was time taken to transfer patients. A shorter DDI was not significantly associated with improved perinatal outcomes. The majority (88.9%) of women had general anaesthesia (GA) for category-one CS. Of those who had an epidural catheter already in situ (34.4%), 25.6% had successful epidural extension. GA was associated with shorter DDI, but worse perinatal outcomes than regional anaesthesia (RA).Conclusions:Our ‘crash’ CS protocol achieved 100% of deliveries within 30 min. The majority (88.9%) of the patients had GA for category-one CS. GA was found to be associated with shorter anaesthesia and operation times, but poorer perinatal outcomes compared to RA.